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Druid vs Singer: What are the differences?
Developers describe Druid as "Fast column-oriented distributed data store". Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations. On the other hand, Singer is detailed as "Simple, Composable, Open Source ETL". Singer powers data extraction and consolidation for all of your organization’s tools: advertising platforms, web analytics, payment processors, email service providers, marketing automation, databases, and more.
Druid and Singer can be categorized as "Big Data" tools.
Druid and Singer are both open source tools. It seems that Druid with 8.31K GitHub stars and 2.08K forks on GitHub has more adoption than Singer with 178 GitHub stars and 40 GitHub forks.
Pros of Druid
- Real Time Aggregations15
- Batch and Real-Time Ingestion6
- OLAP5
- OLAP + OLTP3
- Combining stream and historical analytics2
- OLTP1
Pros of Singer
- Multiple inputs "taps"1
- Open source1
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Cons of Druid
- Limited sql support3
- Joins are not supported well2
- Complexity1
Cons of Singer
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What is Druid?
What is Singer?
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What companies use Singer?
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